Journal ArticleDOI
Model-based recognition in robot vision
Roland T. Chin,Charles R. Dyer +1 more
Reads0
Chats0
TLDR
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision, and an evaluation and comparison of existing industrial part- recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.Abstract:
This paper presents a comparative study and survey of model-based object-recognition algorithms for robot vision. The goal of these algorithms is to recognize the identity, position, and orientation of randomly oriented industrial parts. In one form this is commonly referred to as the "bin-picking" problem, in which the parts to be recognized are presented in a jumbled bin. The paper is organized according to 2-D, 2½-D, and 3-D object representations, which are used as the basis for the recognition algorithms. Three central issues common to each category, namely, feature extraction, modeling, and matching, are examined in detail. An evaluation and comparison of existing industrial part-recognition systems and algorithms is given, providing insights for progress toward future robot vision systems.read more
Citations
More filters
Journal ArticleDOI
A method for registration of 3-D shapes
Paul J. Besl,H.D. McKay +1 more
TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
Journal ArticleDOI
Comparing images using the Hausdorff distance
TL;DR: Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented and it is shown that the method extends naturally to the problem of comparing a portion of a model against an image.
Journal ArticleDOI
Neural network-based face detection
TL;DR: A neural network-based upright frontal face detection system that arbitrates between multiple networks to improve performance over a single network, and a straightforward procedure for aligning positive face examples for training.
Journal ArticleDOI
Alignment by Maximization of Mutual Information
Paul A. Viola,William M. Wells +1 more
TL;DR: A new information-theoretic approach is presented for finding the pose of an object in an image that works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation.
Proceedings ArticleDOI
Method for registration of 3-D shapes
Paul J. Besl,Neil David Mckay +1 more
TL;DR: In this paper, the authors describe a general purpose representation independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
References
More filters
Book ChapterDOI
Processing of Binary Images
P. W. Kitchin,A. Pugh +1 more
TL;DR: This paper is tutorial in nature and gives a treatment of the implementation of edge following algorithms based on Freeman chain coding, which has direct relevance to applications of robot vision even if the original picture is captured as a grey scale image.
Journal ArticleDOI
Error Analysis of Surface Normals Determined by Radiometry
TL;DR: In this article, the surface normals are computed from three images of a workpiece taken under three distinct lighting conditions without requiring surface continuity, and the surface angles off the camera axis can be computed within 5°, except at edge pixels.
Journal ArticleDOI
Visual Inspection Automation
TL;DR: This research presents a meta-modelling framework for designing new products specifically for automated visual inspection that combines machine learning, artificial intelligence, and reinforcement learning.
Book ChapterDOI
Model-Driven Vision for Industrial Automation
TL;DR: The state-of-the-art in image processing techniques, the reduced cost and size and higher reliability of image sensors, and the trend toward low-priced, yet high-performance micro- and mini-processors seems to indicate that the time is “ripe” for the introduction of complex vision tasks to industry.
Proceedings Article
Edge finding, segmentation of edges and recognition of complex objects
TL;DR: This paper describes an approach to the recognition of real-world objects such as books or a telephone on a desk with edge finding process which extracts edges of curved objects from light intensity data, and segmentation of the edges into straight lines or elliptic curves.